Back

The Rab32-LRMDA-Retriever Complex is a Key Regulator of Intestinal Immune Homeostasis

Song, R.; Ngoka, C.; Singla, a.; Kramer, D. A.; Diwaker, A.; Boesch, D. J.; Liu, Q.; Moresco, J. J.; Beutler, B.; Reinecker, H.-C.; Burstein, E.; Chen, B.; Turer, E.

2025-07-21 immunology
10.1101/2025.07.16.665158 bioRxiv
Show abstract

Maintaining intestinal homeostasis relies on the intricate interplay among the mucosal epithelium, immune system, and host microbiome. A key question is how innate immune cells sense and process microbes in the gut lumen, eliciting appropriate protective responses without causing tissue injury. Clearance of invading microbes and initiation of downstream inflammatory responses are central to this process and require proper function of the endolysosomal system. Dysfunction of this system can predispose the host to chronic inflammatory disorders and acute infections. Here, through forward genetic screening of N-ethyl-N-nitrosourea (ENU)-mutagenized mice and CRISPR/Cas9 validation, we identify Lrmda, encoding leucine-rich melanocyte differentiation-associated protein (LRMDA), as a key regulator of intestinal homeostasis. Using hematopoietic chimera and conditional knockouts, we show that LRMDA functions primarily in CD11c+ cells, including mucosal dendritic cells (DCs) and macrophages, but not in non-hematopoietic cells. Proteomic, cellular, and biochemical analyses reveal that LRMDA directly and cooperatively interacts with the endolysosome-specific small GTPase Rab32 and the endosomal recycling complex Retriever. Loss of LRMDA or Retriever function increases susceptibility to dextran sodium sulfate (DSS)-induced colitis and impairs clearance of Listeria monocytogenes. Together, our findings establish the Rab32-LRMDA-Retriever complex as a critical regulator of endolysosomal trafficking in innate immune cells, essential for maintaining intestinal immune homeostasis.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.